Reprint

Modeling Forest Response to Climate Change

Edited by
August 2024
266 pages
  • ISBN978-3-7258-1757-3 (Hardback)
  • ISBN978-3-7258-1758-0 (PDF)
https://doi.org/10.3390/books978-3-7258-1758-0 (registering)

Print copies available soon

This book is a reprint of the Special Issue Modeling Forest Response to Climate Change that was published in

Biology & Life Sciences
Environmental & Earth Sciences
Summary

The uncertainties surrounding climate change raise crucial questions about the ability of forest ecosystems to buffer against current and future climate-induced global changes while continuing to provide essential ecosystem services, as demanded by society and advocated by future policies such as the European Green Deal. Climate-induced extremes could profoundly affect medium- to long-term forest dynamics—including growth, competition, and mortality—along with forest structure and biodiversity. In this era of unprecedented climate shifts, understanding the intricate responses of forest ecosystems to these changes is paramount. In this Special Issue, we collected 13 studies that introduce new methods, novel applications, and innovative designs to: i) model the impacts of climate change on medium- to long-term forest dynamics; ii) assess the impacts of climate change on the delivery of crucial ecosystem services across all forest ecosystems; and iii) analyze, assess, and quantify the impact of climate-induced disturbances on the forest carbon cycle, water dynamics, and overall forest productivity, utilizing data-driven, modelling, and dynamic approaches.

Format
  • Hardback
License and Copyright
© 2024 by the authors; CC BY-NC-ND license
Keywords
height growth functions; dynamic site index models; climatic effects on tree growth; nonlinear height growth models; stand/top height; ecological model; biomass volume; carbon dioxide; optimal control; numerical simulation; climate change; boreal forest; spruce forest; Picea jezoensis; species distribution modeling; Last Glacial Maximum; Northeast Asia; Helleborus thibetanus; species distribution; climate change; bioclimatic variables; forest biomass modeling; 3-PG model; LSTM; biomass compatibility; forest thinning; CO2 emission; forest soils; hydrothermal regime; carbon content; long-term observations; humidity/aridity level; climate change; statistical modeling; climate change; environmental factors; introduction; Magnolia wufengensis; species distribution models; suitable habitats; GF-1; image fusion; Swin Transformer; Mask-RCNN; carbon density growth equation; Cunninghamia lanceolata (Lamb.) Hook.; MaxEnt; geographical distribution; environmental factors; human activities; carbon emission level; joint species distribution model; niche; environmental factors; Tjur R2; carbon cycle; climate change; forest age; forest management; carbon stocks; carbon cycle; climate change; process-based model; mean seasonal cycle; forest ecosystems; NDVI; vegetation dynamics; climate change; precipitation; temperature; Equatorial Africa; n/a